38,959 research outputs found

    IEEE Access special section editorial: Artificial intelligence enabled networking

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    With today’s computer networks becoming increasingly dynamic, heterogeneous, and complex, there is great interest in deploying artificial intelligence (AI) based techniques for optimization and management of computer networks. AI techniques—that subsume multidisciplinary techniques from machine learning, optimization theory, game theory, control theory, and meta-heuristics—have long been applied to optimize computer networks in many diverse settings. Such an approach is gaining increased traction with the emergence of novel networking paradigms that promise to simplify network management (e.g., cloud computing, network functions virtualization, and software-defined networking) and provide intelligent services (e.g., future 5G mobile networks). Looking ahead, greater integration of AI into networking architectures can help develop a future vision of cognitive networks that will show network-wide intelligent behavior to solve problems of network heterogeneity, performance, and quality of service (QoS)

    CSS-Tutor: An Intelligent Tutoring System for CSS and HTML

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    In this paper we show how a student can learn the basics of the system databases using (W3school CSS) which was built as intelligent tutoring educational system by using the authoring tool called (ITSB). The learning material contains CSS and HTML. We divided the material in a group of lessons for novice learner which combines relational system and lessons in the process of learning. The student can learn using example of CSS, and types of CSS color. Furthermore, the intelligent tutoring system supports not only lessons; but exercises of different difficult levels for each lesson. When a student finish successfully the first difficulty level in a lesson, the student is allowed to move to the next difficulty level of the exercises of the lesson

    Genuine lab experiences for students in resource constrained environments: The RealLab with integrated intelligent assessment.

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    Laboratory activities are indispensable for developing engineering skills. Computer Aided Learning (CAL) tools can be used to enhance laboratory learning in various ways, the latest approach being the virtual laboratory technique that emulates traditional laboratory processes. This new approach makes it possible to give students complete and genuine laboratory experiences in situations constrained by limited resources in the provision of laboratory facilities and infrastructure and/or where there is need for laboratory education, for large classes, with only one laboratory stand. This may especially be the case in countries in transition. Most existing virtual laboratories are not available for purchase. Where they are, they may not be cost friendly for resource constrained environments. Also, most do not integrate any form of assessment structure. In this paper, we present a very cost friendly virtual laboratory solution for genuine laboratory experiences in resource constrained environments, with integrated intelligent assessment

    An Intelligent Tutoring System for Cloud Computing

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    Intelligent tutoring system (ITS) is a computer system which aims to provide immediate and customized or reactions to learners, usually without the intervention of human teacher's instructions. Secretariats professional to have the common goal of learning a meaningful and effective manner through the use of a variety of computing technologies enabled. There are many examples of professional Secretariats used in both formal education and in professional settings that have proven their capabilities. There is a close relationship between private lessons intelligent, cognitive learning and design theories; and there are ongoing to improve the effectiveness of ITS research. And it aims to find a solution to the problem of over-reliance on students' teachers for quality education. The program aims to provide access to high-quality education to every student, and therefore the reform of the education system as a whole. In this paper, we will use Intelligent Tutoring System Builder (ITSB) to build an education system on cloud computing in terms of the concept of cloud computing and components and how to take advantage of cloud computing in the field

    Experimental and simulation analysis for performance enhancement of elliptical savonius wind turbine by modifying blade shapes

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    Savonius turbines are drag-based rotors which operate due to a pressure difference between the advancing and retreating blades. After going through an exhaustive literature review, it was realized that the Savonius wind turbines are an applicable option at low wind speed areas, where the counterpart of these turbines cannot work efficiently. Nevertheless, the existing design is still under research to make it more applicable in urban areas. Therefore, the research objective was to develop and test an elliptical Savonius wind turbine to improving its performance in terms of power and torque coefficients by modifying blade shapes and overlap ratio. In the beginning, a series of 2D unsteady simulations (CFD-Fluent version 19.1) of the Savonius elliptical turbine has been performed to study the overlap ratio of blades and the effect of the turbulence models. Conventional elliptical Savonius turbine was modified by changing the overlap ratio from the value (OR=0.15) to (OR=0.2) and called as the Model-A. Then, the concave surface of the blade Model-A was modified (as zigzag shape) and called as Model-B. The blade shape of the Model-B was modified by adding bypass channels for each blade to creating new configuration was called the Model-C. The experimental work begins with the manufacturing of the models (A, B and C) of the blade using 3D printing technology. Models were tested by the wind tunnel in Aerodynamic laboratory (UTHM) with four cases of wind velocity. 2D simulation result for Model-A at OR= 0.2, where the increase in maximum power coefficient value obtained was 3.85% and 7.69% compared to overlap ratio (0.15 and 0.1), respectively. The result of the experimental test was obtained the maximum power coefficient (0.296, 0.292, 0.291, and 0.295) at wind velocity (6 m/s, 8 m/s, 9 m/s, and 10 m/s), respectively for Model-B. The Model-C result in the maximum power coefficient (0.28) compared with Model-A (0.26). The 3D unsteady simulation also has been done to visualisation the behaviour of flow around Model-B and it show a good agreement with experimental test results
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